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- W2041488135 abstract "Bounded uncertainty is a major challenge to real life scheduling as it increases the risk and cost depending on the objective function. Bounded uncertainty provides limited information about its nature. It provides only the upper and the lower bounds without information in between, in contrast to probability distributions and fuzzy membership functions. Bratley algorithm is usually used for scheduling with the constraints of earliest start and due-date. It is formulated as 1|r <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>j</sub> , d <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>j</sub> |C <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>max</sub> . The proposed research uses interval computation to minimize the impact of bounded uncertainty of processing times on Bratley's algorithm. It minimizes the uncertainty of the estimate of the objective function. The proposed concept is to do the calculations on the interval values and approximate the end result instead of approximating each interval then doing numerical calculations. This methodology gives a more certain estimate of the objective function." @default.
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- W2041488135 date "2012-09-01" @default.
- W2041488135 modified "2023-09-24" @default.
- W2041488135 title "Minimizing bounded uncertainty impact on scheduling with earliest start and due-date constraints via interval computation" @default.
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- W2041488135 doi "https://doi.org/10.1109/etfa.2012.6489736" @default.
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